System, method and program product for local client device context-aware shared resource and service management

Abstract

A system context aware resource management, method of managing shared resources and services and a computer program product therefor. Client devices, e.g., handheld or mobile devices, request resources from provider computers, e.g., in a cloud environment. The provider computers provide cloud-based personal assistants. Resource requests from client devices may be context related that may be provided in response to a selected context. A resource management system schedules resource processing for requesting mobile client devices, initially, and responds to device context changes by selectively adjusting shared resource job priorities, e.g., creating a new job, pausing or restarting / resuming a respective job.

Description

BACKGROUND OF THE INVENTION[0001]1. Field of the Invention[0002]The present invention is related to allocating resources amongst multiple computers and more particularly to managing and allocating resources for cloud-based personal assistants.[0003]2. Background Description[0004]Recently, cloud computing has offered great opportunities for a broad range of applications. Cloud service providers (e.g., with mainframe computers) share Information Technology (IT) infrastructure with users / clients, connected together over networks in what constitutes a client-cloud system. The shared IT infrastructure (the cloud computers) provides end-user content and support, i.e., supply services and resources and handle data-intensive computing tasks for the clients. This has allowed user client devices to become much more lightweight and mobile and small enough to be hand held. Further, these lightweight, mobile devices still provide users with access to resources managed by the larger shared resour...

AI Technical Summary

Benefits of technology

The invention is a resource system and method that helps manage the timely provisioning of mobile devices based on their local context. This helps ensure that the devices are always ready for use and can quickly respond to changes in their surroundings.

Problems solved by technology

This has resulted in periods of heavy utilization or peaks, e.g., during the workday, and low utilization or valleys, e.g., at night.

In mobile personal assistance environment, however, targeting timely delivery for end-user support content, imposes mobility, dynamic environment and context-sensitivity issues that impact the timing and relevant context of the delivery area, i.e., what are known as “windows of opportunity.”

For example, the cloud may deliver documents for scheduled meetings just prior to, but close to, the scheduled meeting times. Timely delivery, however, not too early and not too late, may overload resources at that time, spiking cloud computing resource utilization and communications requirements.

Jobs, and in particular, complex and intricate jobs were scheduled according to cloud infrastructure (e.g., a server) deadlines, priorities and performance predictions.

However, the variations of the end-user local context have not been considered in adjusting server-based job scheduling.

Consequently, there may be considerable wasted resources from processing existing job content that, because the mobile user's local context has changed, is no longer relevant in the current local context.

For a single mobile device user this waste is insignificant.

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